@inproceedings{c3c735cc0ffc471087dfc218fb9b42b9,
title = "An improved BOW approach using fuzzy feature encoding and visual-word weighting",
abstract = "The bag-of-words (BOW) has become a popular image representation model with successful implementations in visual analysis. Although the original model has been improved in several ways, the utilization of the Fuzzy Set Theory in BOW has not been investigated thoroughly. This paper presents a fuzzy feature encoding approach to address the problems associated with the hard and soft assignments of image features to the visual-words. Our encoding method assigns each image feature to only the first and second closest words in the codebook to overcome the word-uncertainty problem. Moreover, we introduce a new word-weighting scheme for image categories based on image histograms. Experiments conducted on some image datasets show that both methods increase the BOW performance in content based image retrieval.",
author = "Altintakan, {Umit L.} and Adnan Yazici",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015 ; Conference date: 02-08-2015 Through 05-08-2015",
year = "2015",
month = nov,
day = "25",
doi = "10.1109/FUZZ-IEEE.2015.7338108",
language = "English",
series = "IEEE International Conference on Fuzzy Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Adnan Yazici and Pal, {Nikhil R.} and Hisao Ishibuchi and Bulent Tutmez and Chin-Teng Lin and Sousa, {Joao M. C.} and Uzay Kaymak and Trevor Martin",
booktitle = "FUZZ-IEEE 2015 - IEEE International Conference on Fuzzy Systems",
address = "United States",
}